Abstract:

A context-aware smart home energy management (CASHEM) system and method is
disclosed. CASHEM dynamically schedules household energy use to reduce
energy consumption by identifying contextual information within said
household, selecting a comfort of service preference, wherein said
comfort of service preference is based on different said contextual
information, and extracting an appliance use schedule for maximum energy
savings based on said contextual information in light of said comfort of
service preferences, by executing a program instruction in a data
processing apparatus. CASHEM correlates said contextual information with
energy consumption levels to dynamically schedule said appliance based on
an energy-saving condition and a user's comfort. Comfort of service
preferences are gathered by CASHEM by monitoring occupant activity levels
and use of said appliance. CASHEM can also recommend potential energy
savings for a user to modify comfort of service preferences.

Claims:

1. A method for dynamically scheduling household energy use that reduces
wasteful energy consumption, reduces peak electricity demand, integrates
renewable energy and storage technology, and changes a user's behavior to
manage and consume less energy, said method comprising:identifying
contextual information within said household, by executing a program
instruction in a data processing apparatus;identifying a user preference
for comfort and service within said household, by executing a program
that allows said user to indicate said user preference;selecting a
comfort of service preference, wherein said comfort of service preference
is based on different said contextual information and said user
preference, by executing a program instruction in a data processing
apparatus; andextracting an appliance use schedule for maximum energy
savings based on said contextual information, said user preference, and
said comfort of service preference, by executing a program instruction in
a data processing apparatus.

2. The method of claim 1 further comprising extracting a schedule for
using renewable energy sources and storage batteries within said
household, wherein said extracted schedule reflects said contextual
information about demand response, by executing a program instruction in
a data processing apparatus.

3. The method of claim 1 further comprising:monitoring ongoing appliance
use to infer compliance with said appliance use schedule, by executing a
program instruction in a data processing apparatus; anddynamically
modifying said appliance use schedule according to monitored contextual
information and said user's evolving energy use behavior, by executing a
program instruction in a data processing apparatus.

4. The method of claim 1 further comprising correlating said contextual
information with energy consumption levels to dynamically schedule said
appliance based on an energy-saving condition and a user's comfort, by
executing a program instruction in a data processing apparatus.

5. The method of claim 1 further comprising coordinating an energy manager
to perform at least one of the following operations:gathering contextual
information related to environmental conditions;gathering energy supply
type conditions;gathering cost conditions;selecting a comfort of service
preference; andconfiguring an appliance use schedule.

6. The method of claim 5 wherein said energy manager comprises a graphical
user interface and data processing apparatus, wherein said graphical user
interface is configured for at least one of the following
operations:gathering said contextual information related to user activity
and a daily schedule;gathering information about user comfort and service
preferences;displaying energy use feedback to said user;displaying energy
saving opportunities in compliance with said user's evolving
behavior;recommending use of renewable energy source and stored energy
within said household; anddisplaying incentive or motivational
information to said user based on observed energy use behavior and
adaptive to said user's energy use pattern.

7. The method of claim 1 further comprising monitoring said household's
occupant activity levels and use of said appliance for configuring said
appliance use schedule, by executing a program instruction in a data
processing apparatus.

8. The method of claim 1 wherein said contextual information either
entered by said user or via a networked device includes at least one of
the following:current weather information;forecast weather
information;security system information;utility information;renewable
energy-use information;energy storage information;energy supply type;
andutility signals including at least one of the following types of
signals: demand response (DR), real-time-pricing (RTP) information,
time-of-use (TOU) tariff.

9. The method of claim 1 further comprising operating said appliance
according to said appliance use schedule at a recommended level equal to
a comfort of service preference for maximum energy savings, by executing
a program instruction in a data processing apparatus.

10. A system for dynamically scheduling household energy use that reduces
wasteful energy consumption, reduces peak electricity demand, integrates
renewable energy and storage technology, and changes a user's behavior to
manage and consume less energy, said system comprising:a data-processing
apparatus;a module executed by said data-processing apparatus, said
module and said data-processing apparatus being operable in combination
with one another to:identifying contextual information within said
household, by executing a program instruction in a data processing
apparatus;identifying a user preference for comfort and service within
said household, by executing a program that allows said user to indicate
said user preference;selecting a comfort of service preference, wherein
said comfort of service preference is based on different said contextual
information and said user preference, by executing a program instruction
in a data processing apparatus; andextracting an appliance use schedule
for maximum energy savings based on said contextual information, said
user preference, and said comfort of service preference, by executing a
program instruction in a data processing apparatus.

11. The system of claim 10 wherein said module and said data-processing
apparatus are further operable in combination with one another to extract
a schedule for using renewable energy sources and storage batteries in
said household, wherein said extracted schedule reflects said contextual
information about demand response, by executing a program instruction in
a data processing apparatus.

12. The system of claim 10 wherein said module and said data-processing
apparatus are further operable in combination with one another to:monitor
ongoing appliance use to infer compliance with said appliance use
schedule, by executing a program instruction in a data processing
apparatus; anddynamically modify said appliance use schedule according to
monitored contextual information and said user's evolving energy use
behavior, by executing a program instruction in a data processing
apparatus.

13. The system of claim 10 wherein said module and said data-processing
apparatus are further operable in combination with one another to
correlate said contextual information with energy consumption levels to
dynamically schedule said appliance based on an energy-saving condition
and a user's comfort, by executing a program instruction in a data
processing apparatus.

14. The system of claim 10 wherein said module and said data-processing
apparatus are further operable in combination with one another to
coordinate an energy manager to perform at least one of the following
operations:gather contextual information related to environmental
conditions;gather energy supply type conditions;gather cost
conditions;select a comfort of service preference; andconfigure an
appliance use schedule.

15. The system of claim 14 wherein said energy manager comprises a
graphical user interface and data processing apparatus, wherein said
module, said data-processing apparatus, and said graphical user interface
are further operable in combination with one another to:collect said
contextual information related to user activity and a daily
schedule;collect information about user comfort and service
preferences;display energy use feedback to said user;display energy
saving opportunities in compliance with said user's evolving
behavior;recommend use of renewable energy source and stored energy
within said household; anddisplay incentive or motivational information
to said user based on observed energy use behavior and adaptive to said
user's energy use pattern.

16. The system of claim 12 wherein said module and said data-processing
apparatus are further operable in combination with one another to monitor
said household's occupant activity levels and use of said appliance to
configure said appliance use schedule, by executing a program instruction
in a data processing apparatus.

17. The system of claim 12 wherein said contextual information either
entered by said user or via a networked device includes at least one of
the following:current weather information;forecast weather
information;security system information;utility information;renewable
energy-use information;energy storage information;energy supply type;
andutility signals including at least one of the following types of
signals: demand response (DR), real-time-pricing (RTP) information,
time-of-use (TOU) tariff.

18. The system of claim 12 wherein said module and said data-processing
apparatus are further operable in combination with one another to operate
said appliance according to said appliance use schedule at a recommended
level equal to a comfort of service preference for maximum energy
savings, by executing a program instruction in a data processing
apparatus.

19. An apparatus comprising one or more processor readable storage devices
having processor readable code on said processor readable storage
devices, said processor readable code for programming one or more
processor to perform a method for dynamically scheduling household energy
use that reduces wasteful energy consumption, reduces peak electricity
demand, integrates renewable energy and storage technology, and changes
homeowner behavior to manage and consume less energy,
comprising:identifying contextual information within said household, by
executing a program instruction in a data processing
apparatus;identifying a user preference for comfort and service within
said household, by executing a program that allows said user to indicate
said user preference;selecting a comfort of service preference, wherein
said comfort of service preference is based on different said contextual
information and said user preference, by executing a program instruction
in a data processing apparatus; andextracting an appliance use schedule
for maximum energy savings based on said contextual information, said
user preference, and said comfort of service preference, by executing a
program instruction in a data processing apparatus.

20. The apparatus of claim 19 further comprising:a sensor to detect
contextual information;a network; andan energy manager coupled to said
network comprising said sensor for detecting context information, a
display, said data processing apparatus, and a set of instructions for
dynamically scheduling household energy use that reduces wasteful energy
consumption, reduces peak electricity demand, integrates renewable energy
and storage technology, and changes homeowner behavior to manage and
consume less energy.

[0002]Embodiments are generally related to energy management. Embodiments
are additionally related to energy management of household consumer
appliances. Embodiments are further related to a control interface for
energy management of household consumer appliances.

BACKGROUND OF THE INVENTION

[0003]Net zero energy (NZE) homes are structures that combine
state-of-the-art, energy-efficient construction techniques and equipment,
with renewable energy systems to return as much energy as it uses on an
annual basis. To achieve NZE use in a home, a comprehensive energy
reduction strategy is required, including the use of efficient
appliances, renewable energy resources, and efficient home energy
management capable of adapting to the occupant's lifestyle. Energy
management concepts and technologies reduce wasteful energy consumption,
reduce peak electricity demand, integrate renewable energy and storage
technology, and change the occupant's behavior for the occupant to learn
how to manage and consume less energy.

[0004]A home typically uses unmanaged appliances with minimal planning and
inefficient scheduling. It is impossible to formulate a home energy plan
without a holistic view of home occupancy, usage patterns, demand peaks,
or weather effects on home energy usage. Further, without dynamic energy
pricing, current NZE strategies fall short as technology focuses on user
awareness of energy consumption, basic demand response (DR), and fixed
programmable schedules with minimal ability to control and schedule
energy consumption. Current DR solutions for energy usage range from
simple pager-based solutions to sophisticated appliances, with little
homeowner participation or input. Homeowners may try to reduce household
energy use by turning off the air conditioning during certain parts of
the day or heating the pool to lower temperatures. This approach,
however, does not take into account reducing the energy use of all the
appliances and consumer electronics, as a collective system, within a
home. Other apparatuses and techniques exist to facilitate the efficient
operation of the energy consuming devices, including programmable
electronic thermostats and various timers for lighting, water heaters,
and pool heaters. But these apparatuses, do not communicate with each
other through a centralized system to efficiently manage energy use
within a home. Such solutions simply shift energy consumption and do not
help achieve NZE goals.

[0005]A comprehensive home energy use management system is needed to
coordinate efficient and smart appliances, other energy-consuming
devices, and renewable energy resources. This home energy use management
system also needs to recognize and adjust energy use to varying occupancy
levels and conditions within the home. By accommodating to the lifestyle
of the occupants, and properly scheduling use of appliances, a large
percentage of energy can be saved. Therefore, a need exists for a
context-aware smart home energy manager (CASHEM) to coordinate and
conserve energy use in the home, as will be discussed in greater detail
herein.

BRIEF SUMMARY

[0006]The following summary is provided to facilitate an understanding of
some of the innovative features unique to the disclosed embodiment and is
not intended to be a full description. A full appreciation of the various
aspects of the embodiments disclosed herein can be gained by taking into
consideration the entire specification, claims, drawings, and abstract as
a whole.

[0007]It is, therefore one aspect of the disclosed embodiment to provide
for an improved energy management system and method.

[0008]It is another aspect of the disclosed embodiment to provide for an
improved energy management system and method for household consumer
appliances.

[0009]It is a further aspect of the disclosed embodiment to provide for a
control interface for energy management of household consumer appliances.

[0010]The aforementioned aspects and other objectives and advantages can
now be achieved as described herein. A context-aware smart home energy
management (CASHEM) system and method is disclosed. "Context-awareness"
describes the conditions of energy consumption in the house. CASHEM
identifies contextual information within said household, selects a
comfort of service preference based on previously expressed homeowner
preferences, and generates an appliance use schedule for maximum energy
savings based on said contextual information in light of said comfort of
service preferences. It does this by executing a program instruction in a
data processing apparatus. Once running, CASHEM continues to monitor
actual appliance use and identifies additional opportunities for energy
savings that match up with the homeowner's evolving energy use behavior.
Part and parcel to this is the use various incentives to motivate energy
use behavior change in the desired direction. An energy manager display
coordinates and gathers said user preferences to formulate a dynamic
energy-savings plan for a household.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011]The accompanying figures, in which like reference numerals refer to
identical or functionally-similar elements throughout the separate views
and which are incorporated in and form a part of the specification,
further illustrate the invention and, together with the detailed
description of the invention, serve to explain the principles of the
disclosed embodiments.

[0012]FIG. 1 illustrates a schematic view of a software system including
an operating system, application software, and a user interface, in
accordance with the disclosed embodiments;

[0013]FIG. 2 illustrates a schematic view of a data-processing system, in
accordance with the disclosed embodiments;

[0014]FIG. 3 illustrates a graphical representation of a
computer-implemented context-aware smart home energy management system
(CASHEM), in accordance with the disclosed embodiments;

[0015]FIG. 4 illustrates a flow chart illustrating the logical operation
steps of CASHEM's operation, in accordance with the disclosed
embodiments;

[0016]FIGS. 5A-5B illustrates graphical representations model of energy
savings using CASHEM's dynamic scheduling based on various activities, in
accordance with the disclosed embodiments;

[0017]FIGS. 5C-5D illustrates graphical representations model of energy
savings when using CASHEM's dynamic scheduling techniques to provide a
user with a recommended energy savings usage plan, in accordance with the
disclosed embodiments; and

[0018]FIGS. 6A-6E illustrate a graphical user interface (GUI) for
interaction with the context-aware smart home energy management system
(CASHEM), in accordance with the disclosed embodiments.

DETAILED DESCRIPTION

[0019]The particular values and configurations discussed in these
non-limiting examples can be varied and are cited merely to illustrate at
least one embodiment and are not intended to limit the scope thereof.

[0020]FIGS. 1-2 are provided as exemplary diagrams of data-processing
environments in which embodiments of the present invention may be
implemented. It should be appreciated that FIGS. 1-2 are only exemplary
and are not intended to assert or imply any limitation with regard to the
environments in which aspects of embodiments of the disclosed embodiments
may be implemented. Many modifications to the depicted environments may
be made without departing from the spirit and scope of the disclosed
embodiments.

[0021]FIG. 1 illustrates a computer software system 100 for directing the
operation of the data-processing system 200 depicted in FIG. 2. Software
application 104, stored in main memory 202 and on mass storage 207 (as
described in FIG. 2), generally includes a kernel or operating system 101
and a shell or interface 103. One or more application programs, such as
software application 104, may be "loaded" (i.e., transferred from mass
storage 207 into the main memory 202) for execution by the
data-processing system 200. The data-processing system 200 receives user
commands and data through user interface 103; these inputs may then be
acted upon by the data-processing system 100 in accordance with
instructions from operating system module 101 and/or software application
104.

[0022]As illustrated in FIG. 2, the disclosed embodiments may be
implemented in the context of a data-processing system 200 that includes,
for example, a central processor 201, a main memory 202, an input/output
controller 203, a keyboard 204, an input device 205 (e.g., a pointing
device, such as a mouse, track ball, pen device, etc), a display device
206, a mass storage 207 (e.g., a hard disk), and a USB (Universal Serial
Bus) peripheral connection 211. Additional input/output devices, such as
a rendering device 208 (e.g., printer, scanner, fax machine, etc), for
example, may be associated with the data-processing system 200 as
desired. As illustrated, the various components of data-processing system
200 can communicate electronically through a system bus 210 or similar
architecture. The system bus 210 may be, for example, a subsystem that
transfers data between, for example, computer components within
data-processing system 200 or to and from other data-processing devices,
components, computers, etc.

[0023]The following discussion is intended to provide a brief, general
description of suitable computing environments in which the system and
method may be implemented. Although not required, the disclosed
embodiments will be described in the general context of
computer-executable instructions, such as program modules, being executed
by a single computer. In most instances, a "module" constitutes a
software application.

[0024]Generally, program modules include, but are not limited to routines,
subroutines, software applications, programs, objects, components, data
structures, etc., that perform particular tasks or implement particular
abstract data types and instructions. Moreover, those skilled in the art
will appreciate that the disclosed method and system may be practiced
with other computer system configurations, such as, for example,
hand-held devices, multi-processor systems, data networks,
microprocessor-based or programmable consumer electronics, networked PCs,
minicomputers, mainframe computers, servers, and the like.

[0025]Note that the term module as utilized herein may refer to a
collection of routines and data structures that perform a particular task
or implements a particular abstract data type. Modules may be composed of
two parts: an interface, which lists the constants, data types, variable,
and routines that can be accessed by other modules or routines, and an
implementation, which is typically private (accessible only to that
module) and which includes source code that actually implements the
routines in the module. The term module may also simply refer to an
application, such as a computer program designed to assist in the
performance of a specific task, such as word processing, accounting,
inventory management, etc.

[0026]The interface 103 can include, for example, a graphical user
interface (GUI) or an interactive speech interface. The interface 103 can
serve to display results, whereupon a user may supply additional inputs
or terminate a particular session. In some embodiments, operating system
101 and interface 103 can be implemented in the context of a "Windows"
system. It can be appreciated, of course, that other types of systems are
possible. For example, rather than a traditional "Windows" system, other
operation systems, such as, for example, Linux may also be employed with
respect to operating system 101 and interface 103. The software
application 104 can include, for example, an energy use detection and
management module 102 for providing a CASHEM. The energy use detection
and management module 102 can include instructions, such as those of
method 300 and 400 discussed herein with respect to FIGS. 3-4.

[0027]FIGS. 1-2 are thus intended as an example, and not as an
architectural limitation with respect to particular embodiments. Such
embodiments, however, are not limited to any particular application or
any particular computing or data-processing environment. Instead, those
skilled in the art will appreciate that the disclosed system and method
may be advantageously applied to a variety of system and application
software. Moreover, the present invention may be embodied on a variety of
different computing platforms, including Macintosh, UNIX, LINUX, a real
time OS/kernel and the like.

[0028]FIG. 3 illustrates a graphical representation of a
computer-implemented context-aware smart home energy manager (CASHEM)
310, in accordance with the disclosed embodiments. CASHEM recognizes and
adjusts to different conditions around, and within, a house 320, 340,
350, 360 to minimize total energy consumption. Note that in FIGS. 1-9
identical parts or elements are generally indicated by identical
reference numerals. The disclosed embodiments take advantage of
dynamically planning, scheduling and programming the different appliances
of the house based on these different conditions and the expressed user
preferences within the different conditions. The term "appliance" refers
to any device in the home that consumes, stores or produces energy.
Depending on the varying conditions 320, a home's appliances 350, 360 can
operate at lower or higher energy consumption levels based on the comfort
or convenience level demanded by the occupant. Adaptation of the
appliance coordination system can be supported based on monitoring and
analysis of occupant's activity and the use of the appliances. The
appliance tasks can also be shifted at some time in the future to consume
less energy based on the forecasted weather condition 321. CASHEM 310 is
designed to work with existing homes and appliances, and grow its
capabilities as smart appliances and other components are added to the
home. CASHEM 310 can be the hub for communicating with appliances 350,
360 and use information from different operational, environmental, and
energy supply type parameters. As context sensors become available,
CASHEM 310 can use the sensors for enhanced energy management.

[0029]CASHEM 310 integrates renewable energy sources into the home and
reduces overall energy consumption. By increasing the focus on systems
design, integration, and control, CASHEM 310 serves as a central point to
collect information from all available sources and build the big picture
necessary to manage energy consumption. To build the big picture of a
home's energy usage 300, the computer-implemented home network 330
connects a home's energy-use contexts 320, a home's energy manager
displays 340, and a home's appliances, including both 24/7-type
appliances 350 and on-demand appliances 360. The home energy manager 310
connects to a home's energy meter 329 to collect electricity use
information.

[0030]"Context-awareness" describes the conditions of energy consumption
in the house. CASHEM's 310 objective is to identify the current
contextual state 320, 340 350, 360, note the user preference associated
with that current state, and then configure a context-driven,
appliance-use, convenience, or comfort, of service (CoS) model. The CoS
model correlates the different contexts with energy consumption levels,
and dynamically schedules the appliances 350, 360 under the stated
conditions, based on efficient energy consumption and occupancy comfort.
The type and amount of CoS deviation can vary between different
homeowners with homeowners submitting CoS preferences at system
configuration time. CASHEM 310 reduces energy consumption while keeping
the user comfortable by adapting its recommendations to the occupant's
expressed CoS preferences. The system 310 can also monitor and analyze
energy consumption, recommend further energy saving actions, and
engage/motivate the homeowner to adopt those recommendations.

[0031]Contexts 320 that the system 300 gathers to formulate CoS
preferences include, but are not limited to: weather conditions 321, both
current and forecasted; occupancy and occupancy activity information 322;
security system information 323; utility information 324; renewable
energy-use information 325; energy storage information 326; and plug-in
hybrid electric vehicle (PHEV) information 327. CASHEM 310 integrates
on-site energy generation and renewable energy sources 325. With
context-aware characteristics, CASHEM 310 can coordinate use of wind and
solar energy with charging a hybrid electric vehicle to minimize energy
consumption and reduce carbon footprints. Combined heat and power is
becoming practical in some northern climates, while photovoltaic panels
are becoming cost-effective in the southwest. Energy storage,
particularly in the form of plug in hybrid electric vehicles, is also
making its way into homes.

[0033]An energy efficient home can have smart appliances capable of one or
two-way communication with CASHEM 310. The central communications and
data integration allows the home to be treated as a system 300 as opposed
to a collection of independent, non-communicating appliances. CASHEM 310
can coordinate different types of appliances, including both 24/7-type
appliances 350 and on-demand appliances. 24/7-type appliances include
those appliances used nearly twenty-four hours of a day, for seven days a
week. These include cooling 351 and heating 352 units, water heaters 353,
pool pumps and heaters 354, refrigerators and freezers 361. On-demand
appliances 360 include those appliances used less frequently than
24/7-type appliances 350. On-demand appliances include, but are not
limited to: dishwashers 362, lighting 363, consumer electronics, such as
entertainment devices 364, appliances that run off of wireless controlled
outlets 365, including stereos 365A, computing devices 365B, and
televisions 365C. CASHEM can integrate other similar sensors and systems
when additional appliances are used in the home, such as security
systems, smoke detectors, HVAC, structured wiring, energy management, and
video, to provide one integrated system.

[0034]CASHEM 310 alerts users to pending problems through the home's IP
network 330. Condition-based monitoring (CBM) techniques can be scaled
down and integrated in CASHEM 310. Alerts to the homeowner through
various energy manager displays 340 can be as simple as, for example,
"The furnace has run 265 hours since the filter was changed." CASHEM can
use abnormal vibration detection to identify potential problems in HVAC
systems. CASHEM enables two-way communication with the electrical grid
324 to obtain real-time pricing and demand response events via an open
automated demand response (OpenADR) server or other mechanism that
complies with National Institute of Standards and Technology standards.

[0035]By adjusting to the occupant's preferences and behaviors under
different activity or occupancy conditions of the house, appliance energy
consumption is reduced while keeping the occupants satisfied with a
desirable CoS for each appliance under the different conditions. The
capabilities of the system 300 shown in FIG. 3 are best described through
a series of non-limiting CASHEM 310 use cases, as follows:

Example 1

[0036]Sleep mode activation: The homeowner goes to bed early 322. CASHEM
310 is notified by the security system 323, which triggers the HVAC
system 346 to go into "Sleep" mode. CASHEM 310 also enables the
dishwasher 362 and dryer to complete their pending cycles. The water
heater's 353 settings are changed to reflect reduced energy consumption
329. The entertainment devices 364 and lighting 363 are scheduled turn
off to reduce or eliminate energy consumption 329.

Example 2

[0037]Vacation scheduling: Before leaving on vacation 322, the homeowner
notifies CASHEM 310. The online calendar indicates that the homeowner can
be away for a week 322. CASHEM 310 transmits requests to all appliances
350, 360 to either shutdown or switch to vacation mode. Other appliances
350, 360 may be shut down or switched to vacation mode including:
managing the HVAC system 346, setting the water heater 353 and
refrigerator 361 to power saving modes, turning the entertainment system
364 off, lowering the set point on the pool heater and pump 354 and
turning off lighting 363, as appropriate. Later in the week, CASHEM 310
is notified of the Homeowner's impending return 322 through an SMS text
message on a Smartphone 343, or an e-mail or Tweet® on a computer
device connected to the internet 345b. In response, CASHEM 310 prepares
the home for a homeowner's arrival.

Example 3

[0038]Convenience of Service: CASHEM 310 is aware of the homeowner's CoS
requirements. The homeowner prioritized on the side of energy
conservation. During the cooling season 321, CASHEM 310 looks for
opportunities to bring in outside air 325 whenever feasible instead of
running the air conditioner 351 even though this can affect humidity
levels in the home.

Example 4

[0039]Adaptation of Schedule for 24/7 Appliances 350: CASHEM 310 noted
that the homeowner's schedule has changed 322 due to seasonal factors.
CASHEM 310 determines a new energy-usage schedule that better reflects
the energy usage of the home 322 and presents it to the homeowner. With
the homeowner's concurrence, the new schedule is put into trial service.
Later the new schedule is accepted as a permanent energy usage schedule.

Example 5

[0040]Adaptation for On-Demand Appliances 360: CASHEM 310 has identified
that the dishwasher 362 is generally run after dinner 322 with high CoS
settings. Given time-of-use pricing and the desire of the Homeowner to
conserve energy 329, CASHEM 310 recommends using the dishwasher's 362
delay feature to start washing after the lower prices set in. It also
suggests using air drying mode, since the clean dishes are not needed
until the morning.

Example 6

[0041]Predictive Load Management: It is Friday and the weather 321 is
expected to be unusually hot. The utilities 324 issued a peak pricing
alert for the afternoon, but the homeowner generally works from home 322
on Fridays. CASHEM 310 anticipates cooling needs and pre-cools 351 the
house during the morning hours on Friday to reduce the load during peak
hours, and raises the set point of the HVAC system 346.

Example 7

[0042]Demand response and dynamic pricing: CASHEM 310 is notified that
peak pricing can be in effect and responds by taking actions pre-approved
by the homeowner to reduce demand on the utilities 324. Typical responses
might include reducing set points of HVAC 346, water heater 353, pool
pump and heater 354, and delaying the start of energy consuming
appliances 350, 360 such as dishwashers 362 and dryers. Depending on the
criticality of the pricing request and the CoS settings, more
conservative actions can be taken.

Example 8

[0043]Renewable energy management: The home is equipped with a small wind
turbine 325 and battery storage 326. During the cooling season, the wind
forecast 321 indicates significant generation potential overnight.
Knowing the off-peak utility pricing and the health and capacity of the
battery 326, CASHEM 310 decides to first charge the battery 326 then uses
the excess energy to pre-cool in anticipation of a hot summer day.

[0044]Illustrated in FIG. 4 is a flow chart illustrating the logical
operation steps of CASHEM's 310 operation, in accordance with the
disclosed embodiments. As illustrated in block 401, the CASHEM process is
initiated. CASHEM 310 first identifies contextual information that
affects the CoS of home appliances, as illustrated in block 402. As
illustrated in block 403, the user selects CoS preferences on the
computer-human graphical user interface 103 (GUI), as shown in FIG. 1.
The GUI is provided to display and capture the occupant's appliance
operation preferences and convenience constraints. Next, the appliances
are configured for the different home conditions using a selected CoS
preference, as illustrated in block 404. CASHEM 310 then extracts an
appliance use schedule to run the appliances at an efficient rate to
guide the occupant to either test or comply with further energy saving
opportunities, as illustrated in block 405. Through data monitoring, the
system can analyze energy consumption under different conditions and
recommend to the user further energy saving opportunities, as illustrated
in block 406. The CASHEM controller continues to process and identify
contextual information and configure appliances, even when the user has
not provided new CoS preferences, as illustrated in block 407.

[0045]CASHEM 310 first identifies contextual information that affects the
CoS of home appliances, as illustrated in block 402. Context describes a
setting or a situation that impacts the energy consumption of an
appliance. Awareness of the context with respect to the occupant or the
home environment is used to significantly reduce energy consumption
without compromising the occupant's comfort and convenience. Recognizing
different types of contexts can dictate development of efficient modes of
operations for home appliances. Three main types of context information
exist as a function of time that potentially affect energy consumption,
as follows:

[0046]Operational conditions: These are mainly driven by the user's
occupancy and can be summarized by short and long term schedule.
According to the user schedule, different user modes can be identified as
a function of time. For example, these user modes include In, Vacation,
At the Office, Sleeping, Party, etc.

[0047]Environmental conditions: This context type is typically related to
the current and predicted weather conditions around the house. If the
current and forecasted weather are known, some appliance systems, such as
HVAC, can potentially utilize efficient operational strategies. Also,
weather information such as sunny or windy conditions can affect the
renewable energy supply use in the home.

[0048]Energy supply type and/or cost conditions: This information is
important for the integration and management of renewable sources. It is
related to the reliability of the current and predicted energy supply
from the available sources of energy. It also includes the different
utility signals including at least one of the following signals: demand
response (DR), real-time-pricing (RTP) information, time-of-use (TOU)
tariff.

[0049]As illustrated in block 403, the user selects CoS preferences. The
primary objective of CASHEM is to reduce the total energy consumption
around the house by providing an integrated and optimal schedule that
reflects the CoS for each appliance at different times of the day. The
gathered context information helps develop a specific CoS level for a
particular home. The CoS settings are driven by the variations in context
types. Based on the homeowner preferences and convenience constraints
under different conditions or context information of the house, CASHEM
knows and recommends the best way of operating the home appliances and
renewable resources while meeting the requested convenience constraint.

[0050]A CoS for renewable resources can also be defined according to the
estimated supply and related uncertainty level of the supplied energy. A
CoS metric is then applied to the different appliances. The CoS level is
related to the time it takes to finish a job, or the thermal comfort in
an environment. The CoS is typically correlated to the amount of energy
consumed. Based on the condition driven by the context, the user can
configure the CoS of an appliance for that particular condition. The CoS
can also provide a range base control versus set point control to provide
the occupant with a choice between comfort vs. energy conservation. For
example, when the occupant is "IN", the CoS is 76+/-2 degrees F.; when
the occupant is "ON VACATION", the CoS is 62+/-4 degrees F.; and, when
the occupant is in the office, the CoS is 70+/-4 degrees F. The
temperature range points are mapped to a CoS metric. The user can change
these CoS values under different supply type modes, such as DR mode from
utilities, solar supply, or wind supply.

[0051]Once a CoS level is developed, a home's appliances are configured,
as illustrated in block 404. The initial operational context extraction
related to homeowner activity or schedule can be implemented using
programmable thermostats. Two approaches are typically used to assess
context information: direct sensing measurements and indirect, inferred
by integrating information from multiple sensors. The static schedule can
be enhanced by making use of more accurate context extraction that is
related to the user's activity. Home appliances are first categorized
under two distinct categories, either as on-demand or 24/7 appliances,
before developing a CoS level, as follows:

[0052]On demand (OD) appliances are activated randomly, or scheduled by
external trigger. OD appliances include clothes washers and dryers,
dishwashers, televisions, lighting, etc. These systems generally have
discrete modes of operation. For on-demand appliances, the task is to
correlate the convenience constraints, typically time range of use, to
the energy consumption for the discrete modes of operation. In general,
the goal for the OD appliances is to move to a lower CoS for the given
condition, or move the task to a different time of the day. For example,
CASHEM can recommend washing dishes in three hours instead of two when
the user is IN, or move the task to "SLEEP" time and wash the dishes in 5
hours.

[0053]For 24/7 appliances, the energy savings can be achieved by
recommending a lower CoS for a given condition or reducing the time of
the highest quality conditions. For example, a user could either lower
the heating set point from 72 to 68 deg F. for "IN" or shrink the "IN"
time to 7 hours instead of 8 hours based on occupancy data. 24/7
appliances generally have continuous modes of operation, such as
controlling to a set point. These appliances also have transitional modes
of operations that move from one set point to another, such as
pre-heating or pre-cooling modes. 24/7 appliances include equipments such
as HVAC systems, water heaters, pool heaters and pool pumps. The task for
the 24/7 appliances can be similar to the on-demand appliances. Weather
conditions, however, can affect the relationship and need to be included
in the assignment of a CoS analysis. For example, to maintain 76 degrees
F. for cooling conditions, ventilation can be provided if the outdoor
temperature is low. An example of CoS for heating and cooling is a
comfort index that can be calculated based on temperature or more broadly
based on a predicted mean vote (PMV) (**) index that is based on actual
temperature, humidity, wind velocity, user activity and clothing. Some of
these parameters can be configured or estimated seasonally. The user can
indicate his or her tolerance of comfort range based on activity,
weather, and energy supply type.

[0054]As illustrated in block 405, CASHEM then extracts an appliance use
schedule. Under a given CoS, CASHEM can then select the best mode for a
particular appliance in each category and estimate the energy consumed
under a given CoS. A static schedule is developed first. Typically, the
static schedule during the initial setup results in adherence to CoS
preferences and lower energy savings. CASHEM can also evaluate the cost
of energy and recommend a more efficient schedule based on energy cost
while maintaining homeowner satisfaction. In other cases, the schedule
can deviate enough that the unhappy user can turn off the scheduling
mode. CASHEM can reduce peaks using a combination of range base control
and load shifting via predicted scheduling. When a demand peak is
signaled, CASHEM can automatically shed loads based on information from
the homeowner. CASHEM can supervise and properly schedule all the
appliances during demand response by multiple set point strategy for
example, delaying running the dehumidifier until well after the peak
load. For additional energy savings, CASHEM can respond to non-scheduled
events requested by the user.

[0055]As illustrated in block 406, CASHEM provides the user with
recommended energy-saving opportunities based on the data collected and
user-inputted CoS preferences. CASHEM provides recommendation to the user
to educate the user on current energy savings and future modifications to
CoS preferences to further increase energy savings. The process ends, as
illustrated in block 407.

[0056]FIGS. 5A-5B illustrate graphical representations of energy savings
using CASHEM's dynamic scheduling based on various activities 511. For
example, FIG. 5A illustrates energy savings when using CASHEM 510 based
on user's activity levels 511. CoS preferences for different activity
levels 511 are used to program 501 the energy-use levels of various
appliances over a twenty-four hour period. A user programs 501 energy use
levels for "Sleep" modes 512, "In" modes 513, an "Away" mode 514, and a
"Swim" mode 515, for example. CASHEM dynamically schedules actual energy
use 502 based on these CoS preferences for particular activities 511, but
also incorporates energy saving techniques discussed herein. Therefore,
CASHEM lowers actual energy use 502 for all scheduled modes 512-515, as
illustrated in FIG. 5B. During sleep modes 512, energy use is lower than
energy use during "In" 513 and "Swim" 515 modes. CASHEM's dynamical
scheduling for lower energy use results in energy savings 522 especially
during modes of higher energy use.

[0058]CoS preferences and CASHEM options are programmed using a graphical
user interface (GUI), as illustrated in FIGS. 6A-6E. FIG. 6A illustrates
a GUI 610-650 for display of CASHEM options, in accordance with the
disclosed embodiments. Note that the GUI 610, 620, 630, 640, and/or 650
can be implemented utilizing a GUI such as, for example, the interface
103 depicted in FIG. 1 herein, and may be provided by a module, such as,
for example, module 102 (i.e., a software application). GUI 610, 620,
630, 640, and/or 650 can be displayed via a display device such as a
monitor 206 depicted in FIG. 2. In the illustrated figures herein, the
depicted GUI can be implemented in the context of a GUI "window". Note
that in computing, a GUI window is generally a visual area containing
some type of user interface (e.g., GUI 103). Such a "window" usually (but
not always) possesses a rectangular shape, and displays the output of and
may allow input to one or more processes. Such windows are primarily
associated with graphical displays, where they can be manipulated with a
mouse cursor, such as, for example, the pointing device 205 depicted in
FIG. 2. The user may use a mouse, joystick, light pen, roller-ball,
keyboard, finger or other peripheral devices for manipulating the
pointing device 205 over the GUI 610. For example, CASHEM options
directly on the GUI 610. A GUI using windows as one of its main
"metaphors" is often referred to as a windowing system.

[0059]The GUI 610-650 may include one or more active windows or panes. In
one implementation, four primary panes may be provided, including a
CASHEM query pane 601, a query response selection pane 602, a "Back" pane
603 to skip back to the previous GUI display window, and a "Next" pane
604 to move forward to the next GUI display window. These will be
discussed in more detail below. Other windows and panes may similarly be
provided. Various mechanisms for minimizing, maximizing, moving, and/or
changing the dimensions or the individual panes, may be provided as
typically found in a windows environment.

[0060]The disclosed GUI 610-650 uses a simple question and answer paradigm
to account for wide variations in occupants' perception, definitions, and
tolerance of different comfort levels. Therefore, one of the keys to
acceptance and compliance with CASHEM's energy-saving recommendations is
to tailor the energy tradeoffs to individual homeowners. CASHEM initially
extracts schedules for every appliance and the related CoS range from the
homeowner in a series of interview questions presented on the GUI
610-650. Thus, the homeowner does not need to be a programmer to
implement an energy-savings plan. With the success of the system riding
on the computer-human interaction, a homeowner interface to CASHEM
engages individual homeowners to indicate their own personal constraints
for comfort and convenience, provides a simple paradigm for homeowners to
review and understand energy management recommendations made by the
system, and communicates the value of these recommendations, thereby
motivating the homeowner to comply. Improper use of programmable GUI's
can reduce or completely eliminate energy savings, so occupants need easy
to use, innovative GUI designs for programmable thermostats, for example,
to ensure energy savings.

[0061]CASHEM poses queries 611-651 to users and considers all query
responses 612-652 to formulate energy use schedules and recommendations
for every appliance. For example, in FIG. 6A, GUI 610 displays a query
611 asking the user, "When do you prefer to run your dishwasher?" The
user can select a query response 612 indicating the preferred time, or
select the "Back" pane 613 to skip back to the previous query. When the
user makes a selection from the query response pane 612, or selects the
"Next" pane 614 to skip this pane, the GUI 620 display appears as
illustrated in FIG. 6B. The next query 621 displayed in GUI 620 asks the
user, "When do you prefer to use the heat dry feature?" The user can
select a query response 622 indicating the preferred time, or select the
"Back" pane 623 to skip back to the previous query. When the user makes a
selection from the query response pane 622, or selects the "Next" pane
624, the GUI 630 display appears as illustrated in FIG. 6C. The next
query 631 displayed in GUI 630 asks the user, "In running your
dishwasher, how quickly do you prefer to finish the job?" The user can
select a query response 632 indicating the preferred selection, or select
the "Back" pane 633 to skip back to the previous query. When the user
makes a selection from the query response pane 632, or selects the "Next"
pane 634, the GUI 640 display appears as illustrated in FIG. 6D. The next
query 641 displayed in GUI 640 asks the user, "When do you like to run it
fast?" The user can select a query response 642 indicating the preferred
selection, or select the "Back" pane 643 to skip back to the previous
query. When the user makes a selection from the query response pane 642,
or selects the "Next" pane 644, the GUI 650 display appears as
illustrated in FIG. 6E. The next query 651 displayed in GUI 650 asks the
user, "When do you like to run it slowly?" The user can either select a
query response 652 indicating the preferred selection, select the "Back"
pane 653 to skip back to the previous query, or select the "Next" pane
654, for any further queries related to this appliance. This question and
answer process continues for CASHEM to gather enough CoS preferences and
context information to formulate a comprehensive energy-savings schedule
for all appliances within a home.

[0062]It will be appreciated that variations of the above-disclosed and
other features and functions, or alternatives thereof, may be desirably
combined into many other different systems or applications. Also that
various presently unforeseen or unanticipated alternatives,
modifications, variations or improvements therein may be subsequently
made by those skilled in the art which are also intended to be
encompassed by the following claims.